Variable Structure Control of a Piezoelectric Actuator for a Scanning Tunneling Microscope

Bonnail, N.; Tonneau, D.; Jandard, F.; Capolino, Gérard‐André; Dallaporta, H.

doi:10.1109/tie.2004.825266

Cited by 49 publications

(19 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Micro/nano positioning technology is one of the key enabling methodologies for modern scientific and engineering applications including AFM (Atomic Force Microscopy), STM (Scanning Tunnel Microscopy), optical fiber alignment, bio-micro-surgery, bio-nanotechnology, and micro/nano assembly and manipulation [1][2][3][4][5]. It is well known that the static and dynamic characteristics of the micro/nano positioning mechanisms are mainly dependent on the structure of the mechanism and the performance of the actuator [6].…”

Section: Introductionmentioning

confidence: 99%

Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

Guo

Tian

Liu

et al. 2015

Robotics and Computer-Integrated Manufacturing

View full text Add to dashboard Cite

2015)Design and control methodology of a 3-DOF flexure-based mechanism for micro/nanopositioning. Copies of full items can be used for personal research or study, educational, or not-forprofit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.

show abstract

Section: Introductionmentioning

confidence: 99%

Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

Guo

Tian

Liu

et al. 2015

Robotics and Computer-Integrated Manufacturing

View full text Add to dashboard Cite

show abstract

“…7(a) is the tracking result in the y direction, the maximal tracking error and root mean square (RMS) tracking error are 0.0544 μm and 0.0134 μm, respectively, indicating that the feedforward/feedback controller is more effective than the feedforward controller in signal tracking. However, the coupling errors detected by s 2 the x direction and 1.21×10-4 deg and 3.3×10-5 deg in the θ Z direction. Again, the cross-coupling displacement in the y direction is seriously large.…”

Section: The Feedforward/feedback Controllermentioning

confidence: 89%

“…Thus, it is necessary to introduce a dead-zone operator [26] or a cubic polynomial input function [28,29] to compensate such kinds of nonlinearity. The basic dead-zone operator is (2) where S d [u](t) is the output and d is the threshold of the dead-zone operator.…”

Section: -Dof Flexure-based Mechanismmentioning

confidence: 99%

“…Micro/nano positioning is one of the key enabling techniques in the scientific and engineering fields including AFM (Atomic Force Microscopy) [1], STM (Scanning Tunnel Microscopy) [2], optical fiber alignment [3,4], bio-micro-surgery [5,6] and micro-assembly [7,8]. In order to reach the required high precision, the piezo-driven flexure-based mechanism has been widely used due to the large output force and quick response [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An inverse Prandtl–Ishlinskii model based decoupling control methodology for a 3-DOF flexure-based mechanism

Guo

Tian

Liu

et al. 2015

Sensors and Actuators A: Physical

View full text Add to dashboard Cite

Copies of full items can be used for personal research or study, educational, or not-forprofit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. Abstract ： A modified Prandtl-Ishlinskii (P-I) hysteresis model is developed to form the feedforward controller for a 3-DOF flexure-based mechanism. To improve the control accuracy of the P-I hysteresis model, a hybrid structure that includes backlash operators, dead-zone operators and a cubic polynomial function is proposed. Both the rate-dependent hysteresis modeling and adaptive dead-zone thresholds selection method are investigated. System identification was used to obtain the parameters of the newly-developed hysteresis model. Closed-loop control was added to reduce the influence from external disturbances such as vibration and noise, leading to a combined feedforward/feedback control strategy. The cross-axis coupling motion of the 3-DOF flexure-based mechanism has been explored using the established controller. Accordingly, a decoupling feedforward/feedback controller is proposed and implemented to compensate the coupled motion of the moving platform. Experimental tests are reported to examine the tracking capability of the whole system and features of the controller. It is demonstrated that the proposed decoupling control methodology can distinctly reduce the coupling motion of the moving platform and thus improve the positioning accuracy and trajectory tracking capability.

show abstract

“…One of the pivotal requirements in nanotechnology is nanomanipulation, which is required to deliver nanometer level resolution for handling micro-or nano-scaled objects while maintaining other characteristics such as stiffness, force, speed and adequate dynamic range [2] . Due to their nanometer resolution, high stiffness, big driving force and fast response, piezoelectric actuators (PEA) have been recognized as the fundamental elements to actuate the nanomanipulation systems for managing extremely small displacements [3] . However, the potential of these actuators has been impaired by the adverse effects of their highly nonlinear input/output behavior, more specifically, the hysteresis inherent to piezoelectric materials between the applied voltage and the displacement output especially for a relatively long range of motion or high-frequency excitation, resulting in limited accuracy in open-loop control system even instability in the closed-loop control system [4] .…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of a Piezoelectric Actuator with Neural Network Compensating Rate-Dependent Hysteresis

Alici

Shirinzadeh

et al.

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

View full text Add to dashboard Cite

-Piezoelectric actuators (PEA) are the fundamental elements for high-precision high-speed positioning/tracking task in many nanotechnology applications. However, the intrinsic hysteresis observed in PEAs has impaired their potential, specially, the motion accuracy. In this paper, the complicated nonlinear dynamics of PEA including hysteresis, creep, drift and time-delay etc. are treated as a black-box system exhibited as rate-dependent hysteresis. The multi-valued hysteresis is analyzed as a single-valued function so that a neural network (NN) can be built to model the hysteresis and its inversion. A sliding mode controller (SMC) augmented with inverse hysteresis model is then developed to compensate the hysteretic behavior, modeling error and disturbance to improve the positioning/tracking stability and accuracy. The effectiveness of this algorithm experimentally verified through the actual tracking control of a PEA.

show abstract

Variable Structure Control of a Piezoelectric Actuator for a Scanning Tunneling Microscope

Cited by 49 publications

References 7 publications

Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

Design and control methodology of a 3-DOF flexure-based mechanism for micro/nano-positioning

An inverse Prandtl–Ishlinskii model based decoupling control methodology for a 3-DOF flexure-based mechanism

Sliding Mode Control of a Piezoelectric Actuator with Neural Network Compensating Rate-Dependent Hysteresis

Contact Info

Product

Resources

About